OpenRaiser/Intern-Atlas huggingface dataset:
Minimizing Slowdown in Heterogeneous Size-Aware Dispatching Systems (full version)
Venue: arXiv cs.PF 2012
Year: 2012

We consider a system of parallel queues where tasks are assigned (dispatched) to one of the available servers upon arrival. The dispatching decision is based on the full state information, i.e., on the sizes of the new and existing jobs. We are interested in minimizing the so-called mean slowdown criterion corresponding to the mean of the sojourn time divided by the processing time. Assuming no new jobs arrive, the shortest-processing-time-product (SPTP) schedule is known to minimize the slowdown of the existing jobs. The main contribution of this paper is three-fold: 1) To show the optimality of SPTP with respect to slowdown in a single server queue under Poisson arrivals; 2) to derive the so-called size-aware value functions for M/G/1-FIFO/LIFO/SPTP/SPT/SRPT with general holding costs of which the slowdown criterion is a special case; and 3) to utilize the value functions to derive efficient dispatching policies so as to minimize the mean slowdown in a heterogeneous server system. The derived policies offer a significantly better performance than e.g., the size-aware-task-assignment with equal load (SITA-E) and least-work-left (LWL) policies.
A Corpus-based Study of Temporal Signals
Venue: arXiv cs.CL 2012
Year: 2012

Automatic temporal ordering of events described in discourse has been of great interest in recent years. Event orderings are conveyed in text via va rious linguistic mechanisms including the use of expressions such as "before", "after" or "during" that explicitly assert a temporal relation -- temporal signals. In this paper, we investigate the role of temporal signals in temporal relation extraction and provide a quantitative analysis of these expres sions in the TimeBank annotated corpus.
Bayesian Optimal Auctions via Multi- to Single-agent Reduction
Venue: arXiv cs.GT 2012
Year: 2012

We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good (furthermore, it allows an agent's budget and risk preference to be known only privately to the agent). These are the main challenge areas for auction theory. A single-agent problem is to optimize a given objective subject to a constraint on the maximum probability with which each type is allocated, a.k.a., an allocation rule. Our approach is a reduction from multi-agent mechanism design problem to collection of single-agent problems. We focus on maximizing revenue, but our results can be applied to other objectives (e.g., welfare). An optimal multi-agent mechanism can be computed by a linear/convex program on interim allocation rules by simultaneously optimizing several single-agent mechanisms subject to joint feasibility of the allocation rules. For single-unit auctions, Border \citeyearpar{B91} showed that the space of all jointly feasible interim allocation rules for $n$ agents is a $\NumTypes$-dimensional convex polytope which can be specified by $2^\NumTypes$ linear constraints, where $\NumTypes$ is the total number of all agents' types. Consequently, efficiently solving the mechanism design problem requires a separation oracle for the feasibility conditions and also an algorithm for ex-post implementation of the interim allocation rules. We show that the polytope of jointly feasible interim allocation rules is the projection of a higher dimensional polytope which can be specified by only $O(\NumTypes^2)$ linear constraints. Furthermore, our proof shows that finding a preimage of the interim allocation rules in the higher dimensional polytope immediately gives an ex-post implementation.
Multiple Frequency Selection in DVFS-Enabled Processors to Minimize Energy Consumption
Venue: arXiv cs.DC 2012
Year: 2012

In this chapter we focus on slack reclamation and propose a new slack reclamation technique, Multiple Frequency Selection DVFS (MFS-DVFS). The key idea is to execute each task with a linear combination of more than one frequency such that this combination results in using the lowest energy by covering the whole slack time of the task. We have tested our algorithm with both random and real-world application task graphs and compared with the results in previous researches in [9] and [12-13]. The experimental results show that our approach can achieve energy almost identical to the optimum energy saving.
Autonomic Model for Self-Configuring C#.NET Applications
Venue: arXiv cs.OH 2012
Year: 2012

With the advances in computational technologies over the last decade, large organizations have been investing in Information Technology to automate their internal processes to cut costs and efficiently support their business projects. However, this comes to a price. Business requirements always change. Likewise, IT systems constantly evolves as developers make new versions of them, which require endless administrative manual work to customize and configure them, especially if they are being used in different contexts, by different types of users, and for different requirements. Autonomic computing was conceived to provide an answer to these ever-changing requirements. Essentially, autonomic systems are self-configuring, self-healing, self-optimizing, and self-protecting; hence, they can automate all complex IT processes without human intervention. This paper proposes an autonomic model based on Venn diagram and set theory for self-configuring C#.NET applications, namely the self-customization of their GUI, event-handlers, and security permissions. The proposed model does not require altering the source-code of the original application; rather, it uses an XML-based customization file to turn on and off the internal attributes of the application. Experiments conducted on the proposed model, showed a successful automatic customization for C# applications and an effective self-adaption based on dynamic business requirements. As future work, other programming languages such as Java and C++ are to be supported, in addition to other operating systems such as Linux and Mac so as to provide a standard platform-independent autonomic self-configuring model.
A note on triangle partitions
Venue: arXiv cs.DS 2012
Year: 2012

Koivisto studied the partitioning of sets of bounded cardinality. We improve his time analysis somewhat, for the special case of triangle partitions, and obtain a slight improvement.
On the Use of Non-Stationary Policies for Infinite-Horizon Discounted Markov Decision Processes
Venue: arXiv cs.AI 2012
Year: 2012

We consider infinite-horizon $γ$-discounted Markov Decision Processes, for which it is known that there exists a stationary optimal policy. We consider the algorithm Value Iteration and the sequence of policies $π_1,...,π_k$ it implicitely generates until some iteration $k$. We provide performance bounds for non-stationary policies involving the last $m$ generated policies that reduce the state-of-the-art bound for the last stationary policy $π_k$ by a factor $\frac{1-γ}{1-γ^m}$. In particular, the use of non-stationary policies allows to reduce the usual asymptotic performance bounds of Value Iteration with errors bounded by $ε$ at each iteration from $\fracγ{(1-γ)^2}ε$ to $\fracγ{1-γ}ε$, which is significant in the usual situation when $γ$ is close to 1. Given Bellman operators that can only be computed with some error $ε$, a surprising consequence of this result is that the problem of "computing an approximately optimal non-stationary policy" is much simpler than that of "computing an approximately optimal stationary policy", and even slightly simpler than that of "approximately computing the value of some fixed policy", since this last problem only has a guarantee of $\frac{1}{1-γ}ε$.
Optimizing Channel Access for Event-Driven Wireless Sensor Networks: Analysis and Enhancements
Venue: arXiv cs.NI 2012
Year: 2012

We study the problem of medium access control in domain of event-driven wireless sensor networks (WSNs). In this kind of WSN, sensor nodes send data to sink node only when an event occurs in the monitoring area. The nodes in this kind of WSNs encounter correlated traffic as a subset of nodes start sending data by sensing a common event simultaneously. We wish to rethink of medium access control (MAC) for this type of traffic characteristics. For WSNs, many existing MAC protocols utilize the basic CSMA/CA strategy such as IEEE 802.11 Binary Exponential Backoff (BEB) algorithm to handle the collisions among packets when more than one node need to access the channel. We show that this BEB algorithm does not work well without incurring access delay or performance degradation due to increased number of collisions and retransmissions when nodes encounter correlated traffic. Based on above observations in mind, We present a Adaptive Random Backoff (ARB) algorithm that is capable of mitigating the impact of correlated traffic and capable of minimizing the chance of collisions. ARB is based on minor modifications of BEB. We show using numerical analysis that our proposals improve the channel access in terms of latency, throughput, and frame dropping probability as compared with IEEE 802.11 DCF. Simulations using NS-2 network simulator are conducted to validate the analytical results.
On the Feasibility of Network Alignment for Three-Source Three-Destination Multiple Unicast Networks with Delays
Venue: arXiv cs.IT 2012
Year: 2012

A transform approach to network coding was introduced by Bavirisetti et al. (arXiv:1103.3882v3 [cs.IT]) as a tool to view wireline networks with delays as $k$-instantaneous networks (for some large $k$). When the local encoding kernels (LEKs) of the network are varied with every time block of length $k > 1$, the network is said to use block time varying LEKs. In this work, we propose a Precoding Based Network Alignment (PBNA) scheme based on transform approach and block time varying LEKs for three-source three-destination multiple unicast network with delays (3-S 3-D MUN-D). In a recent work, Meng et al. (arXiv:1202.3405v1 [cs.IT]) reduced the infinite set of sufficient conditions for feasibility of PBNA in a three-source three-destination instantaneous multiple unicast network as given by Das et al. (arXiv:1008.0235v1 [cs.IT]) to a finite set and also showed that the conditions are necessary. We show that the conditions of Meng et al. are also necessary and sufficient conditions for feasibility of PBNA based on transform approach and block time varying LEKs for 3-S 3-D MUN-D.
How to solve kSAT in polynomial time
Venue: arXiv cs.CC 2012
Year: 2012

With using of multi-nary logic analytic formulas proposition that "kSAT is in P and could be solved in $O(n^{3.5})$" was proved
A Multi-Agent Prediction Market based on Partially Observable Stochastic Game
Venue: arXiv cs.MA 2012
Year: 2012

We present a novel, game theoretic representation of a multi-agent prediction market using a partially observable stochastic game with information (POSGI). We then describe a correlated equilibrium (CE)-based solution strategy for this game which enables each agent to dynamically calculate the prices at which it should trade a security in the prediction market. We have extended our results to risk averse traders and shown that a Pareto optimal correlated equilibrium strategy can be used to incentively truthful revelations from risk averse agents. Simulation results comparing our CE strategy with five other strategies commonly used in similar markets, with both risk neutral and risk averse agents, show that the CE strategy improves price predictions and provides higher utilities to the agents as compared to other existing strategies.
Small $\ell$-edge-covers in $k$-connected graphs
Venue: arXiv cs.DS 2012
Year: 2012

Let $G=(V,E)$ be a $k$-edge-connected graph with edge costs $\{c(e):e \in E\}$ and let $1 \leq \ell \leq k-1$. We show by a simple and short proof, that $G$ contains an $\ell$-edge cover $I$ such that: $c(I) \leq \frac{\ell}{k}c(E)$ if $G$ is bipartite, or if $\ell |V|$ is even, or if $|E| \geq \frac{k|V|}{2} +\frac{k}{2\ell}$; otherwise, $c(I) \leq (\frac{\ell}{k}+\frac{1}{k|V|})c(E)$. The particular case $\ell=k-1$ and unit costs already includes a result of Cheriyan and Thurimella, that $G$ contains a $(k-1)$-edge-cover of size $|E|-\lfloor |V|/2 \rfloor$. Using our result, we slightly improve the approximation ratios for the {\sf $k$-Connected Subgraph} problem (the node-connectivity version) with uniform and $β$-metric costs. We then consider the dual problem of finding a spanning subgraph of maximum connectivity $k^*$ with a prescribed number of edges. We give an algorithm that computes a $(k^*-1)$-connected subgraph, which is tight, since the problem is NP-hard.
Optimal Linear Joint Source-Channel Coding with Delay Constraint
Venue: arXiv cs.IT 2012
Year: 2012

The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay constraint. It is shown that, under the mean-square error distortion metric, an optimal encoder-decoder pair from the linear and time-invariant (LTI) class can be found by minimization of a convex functional and a spectral factorization. The functional to be minimized is the sum of the well-known cost in a corresponding Wiener filter problem and a new term, which is induced by the channel noise and whose coefficient is the inverse of the channel's signal-to-noise ratio. This result is shown to also hold in the case of vector-valued signals, assuming parallel additive white Gaussian noise channels. It is also shown that optimal LTI encoders and decoders generally require infinite memory, which implies that approximations are necessary. A numerical example is provided, which compares the performance to the lower bound provided by rate-distortion theory.
An Analysis of One-Dimensional Schelling Segregation
Venue: arXiv cs.GT 2012
Year: 2012

We analyze the Schelling model of segregation in which a society of n individuals live in a ring. Each individual is one of two races and is only satisfied with his location so long as at least half his 2w nearest neighbors are of the same race as him. In the dynamics, randomly-chosen unhappy individuals successively swap locations. We consider the average size of monochromatic neighborhoods in the final stable state. Our analysis is the first rigorous analysis of the Schelling dynamics. We note that, in contrast to prior approximate analyses, the final state is nearly integrated: the average size of monochromatic neighborhoods is independent of n and polynomial in w.
PerfXplain: Debugging MapReduce Job Performance
Venue: arXiv cs.DB 2012
Year: 2012

While users today have access to many tools that assist in performing large scale data analysis tasks, understanding the performance characteristics of their parallel computations, such as MapReduce jobs, remains difficult. We present PerfXplain, a system that enables users to ask questions about the relative performances (i.e., runtimes) of pairs of MapReduce jobs. PerfXplain provides a new query language for articulating performance queries and an algorithm for generating explanations from a log of past MapReduce job executions. We formally define the notion of an explanation together with three metrics, relevance, precision, and generality, that measure explanation quality. We present the explanation-generation algorithm based on techniques related to decision-tree building. We evaluate the approach on a log of past executions on Amazon EC2, and show that our approach can generate quality explanations, outperforming two naive explanation-generation methods.
Uncertain Centroid based Partitional Clustering of Uncertain Data
Venue: arXiv cs.DB 2012
Year: 2012

Clustering uncertain data has emerged as a challenging task in uncertain data management and mining. Thanks to a computational complexity advantage over other clustering paradigms, partitional clustering has been particularly studied and a number of algorithms have been developed. While existing proposals differ mainly in the notions of cluster centroid and clustering objective function, little attention has been given to an analysis of their characteristics and limits. In this work, we theoretically investigate major existing methods of partitional clustering, and alternatively propose a well-founded approach to clustering uncertain data based on a novel notion of cluster centroid. A cluster centroid is seen as an uncertain object defined in terms of a random variable whose realizations are derived based on all deterministic representations of the objects to be clustered. As demonstrated theoretically and experimentally, this allows for better representing a cluster of uncertain objects, thus supporting a consistently improved clustering performance while maintaining comparable efficiency with existing partitional clustering algorithms.
Barriers in Concurrent Separation Logic: Now With Tool Support!
Venue: arXiv cs.LO 2012
Year: 2012

We develop and prove sound a concurrent separation logic for Pthreads-style barriers. Although Pthreads barriers are widely used in systems, and separation logic is widely used for verification, there has not been any effort to combine the two. Unlike locks and critical sections, Pthreads barriers enable simultaneous resource redistribution between multiple threads and are inherently stateful, leading to significant complications in the design of the logic and its soundness proof. We show how our logic can be applied to a specific example program in a modular way. Our proofs are machine-checked in Coq. We showcase a program verification toolset that automatically applies the logic rules and discharges the associated proof obligations.
General Analysis Tool Box for Controlled Perturbation
Venue: arXiv cs.CG 2012
Year: 2012

The implementation of reliable and efficient geometric algorithms is a challenging task. The reason is the following conflict: On the one hand, computing with rounded arithmetic may question the reliability of programs while, on the other hand, computing with exact arithmetic may be too expensive and hence inefficient. One solution is the implementation of controlled perturbation algorithms which combine the speed of floating-point arithmetic with a protection mechanism that guarantees reliability, nonetheless. This paper is concerned with the performance analysis of controlled perturbation algorithms in theory. We answer this question with the presentation of a general analysis tool box. This tool box is separated into independent components which are presented individually with their interfaces. This way, the tool box supports alternative approaches for the derivation of the most crucial bounds. We present three approaches for this task. Furthermore, we have thoroughly reworked the concept of controlled perturbation in order to include rational function based predicates into the theory; polynomial based predicates are included anyway. Even more we introduce object-preserving perturbations. Moreover, the tool box is designed such that it reflects the actual behavior of the controlled perturbation algorithm at hand without any simplifying assumptions.
Signalling Competition and Social Welfare (Working Paper)
Venue: arXiv cs.GT 2012
Year: 2012

We consider an environment where sellers compete over buyers. All sellers are a-priori identical and strategically signal buyers about the product they sell. In a setting motivated by on-line advertising in display ad exchanges, where firms use second price auctions, a firm's strategy is a decision about its signaling scheme for a stream of goods (e.g. user impressions), and a buyer's strategy is a selection among the firms. In this setting, a single seller will typically provide partial information and consequently a product may be allocated inefficiently. Intuitively, competition among sellers may induce sellers to provide more information in order to attract buyers and thus increase efficiency. Surprisingly, we show that such a competition among firms may yield significant loss in consumers' social welfare with respect to the monopolistic setting. Although we also show that in some cases the competitive setting yields gain in social welfare, we provide a tight bound on that gain, which is shown to be small in respect to the above possible loss. Our model is tightly connected with the literature on bundling in auctions.
Optimal Linear Control over Channels with Signal-to-Noise Ratio Constraints
Venue: arXiv cs.SY 2012
Year: 2012

We consider a networked control system where a linear time-invariant (LTI) plant, subject to a stochastic disturbance, is controlled over a communication channel with colored noise and a signal-to-noise ratio (SNR) constraint. The controller is based on output feedback and consists of an encoder that measures the plant output and transmits over the channel, and a decoder that receives the channel output and issues the control signal. The objective is to stabilize the plant and minimize a quadratic cost function, subject to the SNR constraint. It is shown that optimal LTI controllers can be obtained by solving a convex optimization problem in the Youla parameter and performing a spectral factorization. The functional to minimize is a sum of two terms: the first is the cost in the classical linear quadratic control problem and the second is a new term that is induced by the channel noise. %todo ta bort meningen? A necessary and sufficient condition on the SNR for stabilization by an LTI controller follows directly from a constraint of the optimization problem. It is shown how the minimization can be approximated by a semidefinite program. The solution is finally illustrated by a numerical example.
Blind Null-space Tracking for MIMO Underlay Cognitive Radio Networks
Venue: arXiv cs.IT 2012
Year: 2012

Blind Null Space Learning (BNSL) has recently been proposed for fast and accurate learning of the null-space associated with the channel matrix between a secondary transmitter and a primary receiver. In this paper we propose a channel tracking enhancement of the algorithm, namely the Blind Null Space Tracking (BNST) algorithm that allows transmission of information to the Secondary Receiver (SR) while simultaneously learning the null-space of the time-varying target channel. Specifically, the enhanced algorithm initially performs a BNSL sweep in order to acquire the null space. Then, it performs modified Jacobi rotations such that the induced interference to the primary receiver is kept lower than a given threshold $P_{Th}$ with probability $p$ while information is transmitted to the SR simultaneously. We present simulation results indicating that the proposed approach has strictly better performance over the BNSL algorithm for channels with independent Rayleigh fading with a small Doppler frequency.
Unique Decoding of Plane AG Codes Revisited
Venue: arXiv cs.IT 2012
Year: 2012

We reformulate a recently introduced interpolation-based unique decoding algorithm of algebraic geometry codes using the theory of Gröbner bases of modules on the coordinate ring of the base curve. With the same decoding performance, the new algorithm has a more conceptual description that lets us better understand the majority voting procedure central in the interpolation-based unique decoding.
Estimating Rigid Transformation Between Two Range Maps Using Expectation Maximization Algorithm
Venue: arXiv cs.RO 2012
Year: 2012

We address the problem of estimating a rigid transformation between two point sets, which is a key module for target tracking system using Light Detection And Ranging (LiDAR). A fast implementation of Expectation-maximization (EM) algorithm is presented whose complexity is O(N) with $N$ the number of scan points.